The very notion of AI for litigators has moved from a scary, futuristic concept to a daily reality. Whether you’re drafting documents, managing cases, or communicating with clients, AI-powered tools are becoming an integral part of litigation practice.
That means now is the time for litigators to understand both the benefits and the risks of using artificial intelligence in legal practice.
Used well, AI can automate repetitive tasks, improve efficiency, and reduce errors.
Used poorly, it can put your practice and your clients at risk.
The difference lies in understanding the difference between tools which are purpose-built for the legal profession and general-use platforms that should be handled with caution.
In this article, we’ll look at the best ways to use AI in a litigation practice, common mistakes to avoid, and the top tools that can help you harness artificial intelligence responsibly.
Before you use AI for litigation
Before diving into specific tools, it’s important to understand the overall tech environment we’re facing.
Not all AI is created equal. Be thoughtful about how, when, and why you bring artificial intelligence into your practice.
Know the difference between general and legal-specific AI
There’s a big gap between consumer-facing AI platforms like ChatGPT and intentionally built AI tools for litigation.
You can use both. Just not in the same ways.
General large language models (LLMs) can be useful for low-risk tasks such as summarizing non-sensitive text or generating first drafts of internal content. But they are “black box” systems, which means you have limited visibility into how data is processed or stored.
By contrast, litigation-focused tools like Lexis+ AI, CoCounsel, or InfoTrack Intelligence are built with security, compliance, and attorney workflows in mind.
Litigation tools with AI are less likely to create ethical pitfalls because they’re specifically engineered to handle sensitive legal data.
Establish a firm-wide AI policy
Even the best AI for litigation can cause problems if attorneys use it inconsistently.
Every law firm should have a clear policy outlining acceptable and unacceptable use cases for AI. A good policy typically addresses:
- Data security: Never input privileged or client-sensitive information into consumer LLMs.
- Transparency: Attorneys and staff should disclose when AI was used in the creation of a document.
- Policy: Which platforms are sanctioned by the firm and under what circumstances.
For more detail, see InfoTrack’s guide to drafting a law firm AI policy.
Be realistic about the risks
Headlines about AI “hallucinations” and ethical slip-ups are hard to ignore, but most risks are manageable if you use AI responsibly.
The key is understanding limitations (and Ethics Opinions on the issue).
AI is not a substitute for legal reasoning, and it should never replace attorney oversight. By setting guardrails early, litigators can reduce risk and still reap the benefits of efficiency.
The best AI tools for litigation
As noted above, when you’re evaluating AI for your litigation practice, it helps to start with tools designed specifically for legal work because they carry less risk and deliver more direct value.
General AI tools can still be useful, but they require extra caution around data security and ethical compliance.
InfoTrack Intelligence
A leader in litigation tools, InfoTrack Intelligence enables firms to file in 30 seconds or less with far fewer rejections.
How?
When you select your legal documents for filing, the tool uses AI to read and understand those documents. Then, it populates the eFiling fields, including the document types and filing codes to route your submission to the right place.
The first firms that switched from traditional eFiling to InfoTrack Intelligence saw mind-blowing results.
Instead of a few minutes per filing, the entire eFiling process takes just 30 seconds. Firms that made the switch experienced an instant boost in accuracy, which cut their eFiling rejections in half.
InfoTrack also automates expense tracking, integrates with case management systems, and even allows you to order a process serve in under 20 seconds.
For litigators juggling multiple deadlines, the time savings and reduction in manual errors can be transformative.
Assembly Neos
Assembly’s Neos platform is a powerful case management system that uses AI to streamline litigation workflows.
Your daily tasks like document management, calendaring, and client intake are all simpler with Neos. It’s especially powerful for firms that want to establish a workflow and keep everyone in the firm accountable.
One area where Neos is particularly strong is client communications.
You can’t (and shouldn’t) automate human connection. But there’s a lot of stuff that goes into intake and client communication on top of the actual conversations, right?
Neos uses AI to help clients answer their own routine questions about the case. The AI can also quickly summarize what’s happened so far to get you up to speed immediately — a major relief when you’ve got a client on the phone waiting for answers.
Ironclad
While best known as a contract lifecycle management tool, Ironclad offers AI-driven features for litigation teams such as contract review, document automation, precedent analysis, case evaluation, research, discovery, and pre-trial workflows.
If you want to use AI to help with contract management, this is one of those applications that should only be done with tools built for the legal industry.
Ironclad has a great reputation when it comes to security standards, just like their name implies.
Harvey
One of the most talked-about entrants into legal AI, Harvey has positioned itself as a “copilot” for lawyers, with capabilities ranging from drafting memos to analyzing case documents.
While still evolving, it has gained traction among large firms exploring scalable AI for litigation solutions.
If you’re exploring Harvey or any similar legal-focused LLMs, do your homework first. Reviews from actual users are mixed, and some people are still concerned about privacy and data security.
Improvements and updates get released regularly, so if you’re not ready to jump in yet, keep an eye on it. You might change your mind as the team iterates.
Using non-legal AI tools in litigation
Even though the above tools can prove invaluable for law firms, there’s a vast array of AI tools that weren’t built with the legal industry in mind.
General-purpose platforms can save time and boost productivity, but litigators need to approach them with care.
The guiding principles are simple: never input sensitive or privileged information, understand how your data will be used, and confirm that the tool aligns with your ethical obligations.
ChatGPT and other large language models (LLMs)
Tools like ChatGPT, Claude, or Grok are powerful for generating text — but they’re not designed as AI tools for litigation.
- Good use cases: drafting a first pass of a marketing email, rephrasing content for client newsletters, or editing blog posts.
- Bad use cases: conducting legal research, analyzing case law, or drafting motions. These tasks require accuracy, and LLMs are prone to “hallucinations” — generating authoritative-sounding, but incorrect, results. In case you’re still tempted, you might take the time to review cases like Mata v. Avianca, Inc., where lawyers were sanctioned for providing the court with legal citations that were manufactured by AI.
Midjourney and other image generators
Visual tools like Midjourney can be useful for prototyping law firm advertising campaigns or creating graphics for social media.
- Good use cases: designing mock-ups for promotional material, brainstorming website visuals.
- Bad use cases: anything that risks copyright or intellectual property infringement (a growing area of concern for AI-generated art), such as mimicking an existing artist’s style.
Google NotebookLM
Google’s NotebookLM is a powerful tool designed to summarize large sets of notes or documents.
For litigators, it could be used cautiously to synthesize non-privileged material, such as stacks of case law and law review articles on any issue you’re researching.
However, because it’s still an experimental Google product, review your data-handling policies before incorporating it into litigation workflows.
AI notetakers like Otter.ai
AI-driven transcription tools like Otter.ai can be extremely useful for internal meetings or non-confidential brainstorming sessions.
- Good use cases: creating searchable transcripts of team meetings, capturing key points in project updates.
- Bad use cases: recording privileged client conversations or sensitive strategy discussions. Not only could this risk data exposure, but some clients may be uncomfortable with AI transcribers present during confidential meetings.
Conclusion
AI is no longer optional in modern law firms — it’s part of the evolving practice of litigation.
For litigators, the challenge is not whether to use AI, but how to use it responsibly. By starting with legal-specific platforms, establishing clear firm policies, and exercising caution with general-purpose tools, firms can capture the efficiency benefits of AI for litigators while staying within ethical boundaries.
